Provable concept learning for interpretable predictions using variational inference.
Armeen TaebNicolò RuggeriCarina SchnuckFanny YangPublished in: CoRR (2022)
Keyphrases
- concept learning
- variational inference
- bayesian inference
- topic models
- probabilistic model
- probabilistic graphical models
- latent dirichlet allocation
- posterior distribution
- gaussian process
- mixture model
- closed form
- variational methods
- inductive logic programming
- inductive learning
- factor graphs
- approximate inference
- markov networks
- exact inference
- graphical models
- exponential family
- hyperparameters
- latent variables
- parameter estimation
- knowledge acquisition
- information retrieval
- prior information
- generative model
- bayesian framework
- model selection
- co occurrence
- knowledge representation
- probability distribution
- knowledge base